Getting the Digital Agenda Right for Wealth Management

Advisors should start to embrace a smart mix of digital approaches like Amazon recommendation models and automated workflows of previous core competencies.

Even while regulations have piled up during the last few years, wealth management firms have put customer focus back at the top of priorities, especially now that they’ve gained a bit more breathing room in the form of growing assets under management. The goal is to deliver the most relevant, impactful advice that is consumable and cost effective for the client. There are several digital influences now shaping what the best approach is to optimal advice or recommendations. So what should wealth firms be considering?

First, there is online algorithmic money management (or "robo" advisors), which has grabbed top airtime. Many of these sites have actually been building momentum and are driving a wedge in some of the key value propositions traditional wealth managers make. Their goal is to disrupt the delivery and pricing model of personal investing and advice, and I applaud them. The interest in these firms has raised a host of questions, such as their long-term impact and, ultimately, how wealth firms should respond. Key aspects of the robo model that wealth and asset management firms need to be mindful of are:

Algorithmic and automated portfolio management for individuals

Online channel only used for advisor communications

Highly transparent pricing and fees schedules

Advanced self-service tools and access to financial information across channels

Gateway to capture lower-income and youth segments

Next, when looking for best-practices to model customer experience and recommendation, we typically search outside wealth management. And out in front of the customer recommendation discussion (I think of this as advice for wealth firms) you will often find Amazon, LinkedIn, and Netflix. Their smart algorithms, dynamic learning, and execution are often lauded as bleeding-edge examples of capturing value from big data -- particularly when compared with the wealth and asset management industries. These companies have a phenomenal command of analytics in a way that enables them to improve (generate economic value) their customers’ “jobs to be done” and reduce their effort to use their services. Yet, while impressive, I see them as poor yardsticks when compared to wealth management.

The reason for this is that online segments where consumption (retail, movies, reading, etc.) or social networking are the primary product or service, firms can leverage big data, algorithms, and automation for large portions, if not a majority, of their interactions and delivery model. Further, there are different criteria when using services that dictate how consumers or clients engage. For example, one click on Amazon will get you a $25 dollar DVD that hits your door in two days. This is significantly different from weighing the pros and cons of a Roth or traditional IRA, whose worth, value, and use won’t be seen for decades.

In short, you don't make financial decisions as quickly as an Amazon one-click buy.

But can a computer effectively manage the financial nuances of so many individual clients or even the ultra-high-net-worth segment? Many would be inclined to say no, however there is plenty of evidence supporting the opposing side -- most consumers make only slightly informed, or, more accurately, uninformed, decisions with advice that can too often be disjointed and not particularly aligned to individual situations. Further, advisors are stretched, they lack adequate time to manage relationships, and fresh pools of talent are tightening. So which is it? Both. It’s not an “or” situation, rather it’s an “and.”

I wouldn’t ignore the robo advisor model or Amazon recommendation approaches entirely, nor would I adopt them fully in the context of wealth management. Regardless of which segment a wealth firm serves, be it mass affluent, high net worth, young, old, etc., advisors need to automate various functions or workflow and certain aspects of their services. Algorithms, digital marketing, and communications are tools to automate workflow within various channels needed for advisors to reduce the friction of how advice is delivered and consumed and, ultimately, experience improved. The transparency and portfolio management aspects from the robo advisor model should replace a portion of services an advisor may perform for clients. It’s a smart mix of digital approaches and advisor interaction.

This leaves us with the following idea: Embrace the robo advisor model, and consider what advisor services can be digitally in/out-sourced like client portfolio management, rebalancing, news, or alerts. Future success may require abandoning previous core competencies. While account management and customer recommendations/advice cannot be fully automated (not yet at least), there is a balance that needs to be struck. Like Amazon and Netflix, the use of data and analytics is needed to help find what balances of best-practices and profitable frontiers exist, and the tools are available today to dynamically evolve how advisors give better advice. Crafting a strong hybrid digital agenda is an imperative to attain profitable growth and execute against the new set of customer advice standards.

Sean O'Dowd leads the Global Capital Markets program at Teradata for Industry and Marketing Solutions. In this role Sean focuses on industry strategy, marketing and field enablement. Areas of focus span financial market structure, regulations and technologies that impact the ... View Full Bio

Thanks, Sean. Really interesting points about the place of a automated recommendations for today's consumers.

As you mention, I do think people put a bit more thought into their Amazon purchases than a simple one-click buy process might suggest (we compare products, read reviews) and by the same token, clients probably put less work into making investment decisions than they're expected to. Sure, investors are given piles of documents to review, but can only consume (and understand) so much, especially when there are multiple decisions to be made. The robo advisor model helps cut down the options and allows clients to have more targeted interactions with advisors. There can be a happy medium here. Trust in the model is probably most important, the client has to believe it is looking after their best interests.

Great points Becca, and surely in the middle is the likely path of 'man and machine.' I've oversimplified the Amazon example to drive a point, and you hit it precisely, which is to say that I agree people are expected to do more...yet can they? And what behavioral requirements are good criteria when looking at something from a personal finance decision vs a consumption one..is there a difference? Advisors do currently use algos to help them do a number of things and there is certainly more to be done as the needs, access and types of users of wealth services changes.

Trust is an absolute requirement, and you'll find it smack in the middle of most wealth ad campaigns, and proving it is an altogether different task - transparency continues to be a good component to aid the proof process which is one reason why robos seem to be gaining a lot of attention it seems.

It wasn't all bad luck for the capital markets this week: Hedge funds had a decent first quarter despite a slowdown in jobs numbers, BlackRock might be heading into new territory as hedge fund managers take a hard look at their counterparties, and the head of the IMF didn't pull any punches when assessing today's global economy. At least we can admire the nice weather and some of the best quotes of the week.